Processing Method, Device, Storage Medium and Processor for Engine Physical Model

Abstract

The present invention discloses a method, device, storage medium and processor for processing an engine physical model. Among them, the method includes: based on the physical structure of the engine, constructing a complex physical model of the engine, the complex physical model including entity elements corresponding to different parts in the physical structure, and connection elements connected to different entity elements, the connection elements including one of the following: heat conduction elements, heat exchange elements and radiation elements; merging some elements in the complex physical model to obtain multiple merged modules, and there is an associated relationship between the multiple modules and the water temperature and oil temperature of the engine; inputting the operating parameters of the engine under different working conditions into the complex physical model to determine the target pulse spectrum parameters corresponding to the multiple modules; combining the multiple modules and the target pulse spectrum parameters to generate a reduced-order physical model of the engine. The present invention solves the technical problem that the engine physical model constructed in the related art can ensure the model accuracy, but the running speed cannot meet the real-time requirement of the model for virtual calibration.

Description

Technical Field

[0001] The present invention relates to the field of vehicle control, and in particular, to a method, an apparatus, a storage medium, and a processor for processing an engine physical model. Background Art

[0002] The controller-in-the-loop vehicle virtual calibration system mainly consists of a standard hardware-in-the-loop system, a vehicle real-time model, and an external actual controller. Among them, the actual controller includes, but is not limited to: ECU (Electronic Control Unit), TCU (Transmission Control Unit), and HCU (Hybrid Control Unit). After the vehicle model (including, but not limited to: engine, original exhaust, thermal management, aftertreatment, vehicle, motor battery, transmission, and vehicle dynamics) is compiled and downloaded to the real-time machine of the standard hardware-in-the-loop system, the model is connected to the real-time machine through the IO interface model, and a real hard-wired signal (i.e., HW I / O) connection is established with the external actual controller through various signal simulation boards on the standard hardware-in-the-loop system. The controller can collect the signals sent by the model in real time, and the model can also execute various control instructions sent by the controller in real time. The model and the controller form a closed loop through the standard hardware-in-the-loop system. See the appendix for details Figure 1 The controller and the actuator are connected through real hardware signals.

[0003] The controller-in-the-loop vehicle virtual calibration system has extremely high requirements for model accuracy and real-time performance. If the model operation speed is slow, it cannot respond to the controller requirements in real time. If the model accuracy is poor, the virtual calibration result loses its meaning. As a part of the vehicle virtual calibration model, the engine thermal management model naturally also needs to meet the accuracy and real-time performance requirements of the virtual calibration for the model. Due to the limitation of the real-time performance requirements of the virtual calibration for the model, simplified models are usually used for thermal management. Simplified models can meet the real-time performance requirements, but their accuracy is usually poor. The thermal management model built using 1D simulation software can ensure model accuracy, but its running speed cannot meet the real-time performance requirements of the virtual calibration for the model.

[0004] In view of the above problems, no effective solution has been proposed yet. Summary of the Invention

[0005] Embodiments of the present invention provide a method, an apparatus, a storage medium, and a processor for processing an engine physical model, so as to at least solve the technical problem that the constructed engine physical model in the related art can ensure model accuracy, but its running speed cannot meet the real-time performance requirements of the virtual calibration for the model.

[0006] According to one aspect of an embodiment of the present invention, a method for processing an engine physical model is provided, including: constructing a complex physical model of the engine based on the physical structure of the engine, where the complex physical model includes entity elements corresponding to different parts in the physical structure, and connection elements connected to different entity elements, and the connection elements include one of the following: a heat conduction element, a heat exchange element, and a radiation element; merging some elements in the complex physical model to obtain multiple merged modules, where the multiple modules have an associated relationship with the water temperature and oil temperature of the engine; inputting the operating parameters of the engine under different working conditions into the complex physical model to determine the target pulse spectrum parameters corresponding to the multiple modules, where the target pulse spectrum parameters at least include: a heat transfer coefficient, a thermal conductivity coefficient, a radiation coefficient, and a fluid flow rate parameter; combining the multiple modules and the target pulse spectrum parameters to generate a reduced-order physical model of the engine.

[0007] Optionally, constructing a complex physical model of the engine based on the physical structure of the engine includes: determining multiple nodes on the water circuit and oil circuit of the engine based on the physical structure of the engine; constructing the complex physical model based on the digital model parameters, attributes, and characteristic data of each node, and the heat exchange process of each node, where the characteristic data is used to characterize the pressure drop, flow rate, and heat dissipation characteristic data of the fluid at each node.

[0008] Optionally, the multiple modules at least include: a water block, a radiator block, an engine block, a water flow block, an oil block, and a supercharger block.

[0009] Optionally, the input heat of the engine block, the supercharger block, and the oil block includes: the heat input by the combustion heat source, the heat taken away by the water, and the heat dissipated to the air; the input heat of the water block includes: the heat dissipated from the engine block to the water block, and the heat exchanged between the water block and the water flow block; the input temperature based on which the water temperature in the oil block is determined includes: the temperature of the oil block and the water temperature in the engine block; the input temperature based on which the water temperature in the supercharger block is determined includes: the temperature of the supercharger block and the water temperature in the engine block; the input temperature based on which the water temperature in the radiator block is determined includes: the temperature of the ambient air and the water temperature in the engine block.

[0010] Optionally, the water flow block is used to determine the water flow rate flowing through other modules.

[0011] Optionally, after constructing a complex physical model of the engine based on the engine's physical structure, the method further includes: when the engine is operating under a preset working condition, collecting the first measured temperatures of multiple temperature measurement points on the engine through a temperature sensor; when the complex physical model is operating under the preset working condition, obtaining the first simulated temperatures of the multiple temperature measurement points output by the complex physical model; determining whether the accuracy of the complex physical model reaches a first preset accuracy based on the deviation between the first measured temperature and the first simulated temperature; and adjusting the pulse spectrum parameters included in the complex physical model when the accuracy of the complex physical model does not reach the first preset accuracy.

[0012] Optionally, after combining multiple modules and target pulse spectrum parameters to generate a reduced-order physical model of the engine, the method further includes: when the engine is operating under a preset working condition, collecting the second measured temperatures of multiple temperature measurement points on the engine through a temperature sensor; when the reduced-order physical model is operating under the preset working condition, obtaining the second simulated temperatures of the multiple temperature measurement points output by the reduced-order physical model; determining whether the accuracy of the reduced-order physical model reaches a second preset accuracy based on the deviation between the second measured temperature and the second simulated temperature; and adjusting the pulse spectrum parameters included in the reduced-order physical model when the accuracy of the reduced-order physical model does not reach the second preset accuracy.

[0013] According to another aspect of the embodiments of the present invention, there is also provided a processing device for an engine physical model, including: a construction module for constructing a complex physical model of the engine based on the engine's physical structure, where the complex physical model includes entity elements corresponding to different parts in the physical structure and connection elements connected to different entity elements, and the connection elements include one of the following: a heat conduction element, a heat exchange element, and a radiation element; a merging module for merging some elements in the complex physical model to obtain multiple merged modules, where the multiple modules have an associated relationship with the water temperature and oil temperature of the engine; a determination module for inputting the operating parameters of the engine under different working conditions into the complex physical model to determine the target pulse spectrum parameters corresponding to the multiple modules, where the target pulse spectrum parameters at least include: a heat transfer coefficient, a thermal conductivity coefficient, a radiation coefficient, and a fluid flow parameter; and a generation module for combining the multiple modules and the target pulse spectrum parameters to generate a reduced-order physical model of the engine.

[0014] According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, where the computer-readable storage medium includes a stored program, and when the program runs, it controls the device where the computer-readable storage medium is located to execute the processing method of the engine physical model in the above embodiments.

[0015] According to another aspect of the embodiments of the present invention, there is also provided a processor for running a program, and when the program runs, it executes the processing method of the engine physical model in the above embodiments.

[0016] According to another aspect of the embodiments of the present invention, a vehicle is further provided, including the reduced-order physical model in the above embodiments.

[0017] In the embodiments of the present invention, first, a complex physical model of the engine is constructed based on the physical structure of the engine, then some components in the complex physical model are merged to obtain multiple merged modules, and the operating parameters of the engine under different working conditions are input into the complex physical model to determine the target pulse spectrum parameters corresponding to the multiple modules. Finally, the multiple modules and the target pulse spectrum parameters are combined to generate the reduced-order physical model of the engine. It is easy to note that the complex physical model is constructed based on the physical structure of the engine and is reduced in order based on the operating parameters of the engine under different working conditions, achieving the purpose of meeting the real-time requirements of the model for vehicle virtual calibration (controller-in-the-loop), thus realizing the technical effect of simplifying the model, and further solving the technical problem that the physical model of the engine constructed in the related art can ensure the model accuracy but the running speed cannot meet the real-time requirements of the virtual calibration for the model. Description of the Drawings

[0018] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0019] Figure 1 is a schematic diagram of a controller-in-the-loop vehicle virtual calibration system according to the prior art;

[0020] Figure 2 is a flowchart of a processing method for an engine physical model according to an embodiment of the present invention;

[0021] Figure 3 is a flowchart of an optional method for reducing the order of a thermal management model according to an embodiment of the present invention;

[0022] Figure 4 is a schematic diagram of an optional dissected engine physical structure according to an embodiment of the present invention;

[0023] Figure 5 is a schematic diagram of all modules included in an optional reduced-order physical model according to an embodiment of the present invention;

[0024] Figure 6 is a schematic diagram of the water flow relationship between different modules included in an optional reduced-order physical model according to an embodiment of the present invention;

[0025] Figure 7It is a schematic diagram of an optional reduced-order thermal management model and measured data according to an embodiment of the present invention;

[0026] Figure 8 It is a schematic diagram of a processing device for an engine physical model according to an embodiment of the present invention. Detailed implementation manners

[0027] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily need to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0029] The 1D thermal circuit model of the 15TD dual-motor hybrid built by AMESim can simulate the real flow conditions of water and oil, and can also truly reflect the heat exchange conditions on the water and oil circuits, the heat conduction conditions between solid entities, and the heat radiation conditions of the solid to the outside. It is a physical model that can simulate the real flow of engine fluids and the real transfer flow of heat, and this model has high accuracy. However, the operation speed of this model is extremely slow, resulting in the model not meeting the real-time requirements of virtual calibration for the model.

[0030] During the operation of the AMESim model, in order to calculate the heat exchange of the fluid flowing through the path nodes, that is, the heat exchange between the fluid and the contacting hot solid, it is necessary to determine not only the temperature difference between the fluid and the hot solid, but also the contact area between the fluid and the hot solid and the flow state of the fluid. The real simulation of the fluid flow state by the model is exactly the main reason for the slow operation speed of the model.

[0031] To solve the above problems, a traditional reduction method for physical models with complex structures is provided in the related art. This method directly regards some complex structures in the model as a black box. Under reasonable planning of input conditions, the complex physical model is simulated to capture the output of the black box. After obtaining the input and output data, the data is analyzed to directly establish a relationship model based on the input and output data. However, this method does not change the overall composition structure of the model, but only treats the complex structure as a black box, and improves the model operation speed by establishing a data-based model for the black box, resulting in low accuracy of the processing results.

[0032] In order to perform order reduction processing on the physical model built by AMESim, so that it can not only maintain the original model accuracy, but also meet the real-time requirements of the virtual calibration for the model, the present invention can adopt the following principle for order reduction processing:

[0033] For an engine with a determined structure, when calculating the convective heat transfer between fluid and solid, without considering the self-property information of the fluid and solid, the heat transfer amount between the fluid and the solid is mainly related to the fluid flow rate and the temperature difference between the fluid and the hot solid. Among them, when the temperature difference is the same, the larger the flow rate, the larger the heat transfer amount; when the flow rate is the same, the larger the temperature difference, the larger the heat transfer amount. Therefore, it can be considered that the heat transfer amount is a proportional function of the temperature difference, and the proportional coefficient is directly related to the flow rate. At the specified fluid heat transfer node, the average heat transfer proportional coefficient at each flow rate at this node can be determined, so that the heat transfer amount can be directly calculated according to the temperature difference without paying attention to the internal structure details of the heat transfer node. Therefore, multiple heat transfer nodes can be integrated to find the average heat transfer proportional coefficient of the integrated heat transfer node at each flow rate. Compared with the AMESim model, the heat transfer calculation process of the integrated thermal management model will be greatly simplified.

[0034] When the fluid exchanges heat at a specified node on the flow path, it will inevitably cause changes in the temperatures of the fluid and the hot solid. Assuming that the fluid and the hot solid are regarded as a whole respectively, if the comprehensive average specific heat of the fluid and the solid can be determined, then compared with the AMESim model, the calculation of the temperature changes of the fluid and the hot solid will also be simplified.

[0035] During the operation of the AMESim model, the model can simulate the fluid flow state according to the vehicle operation state information and the physical characteristics of the fluid and the flow channel, and then use this model for heat transfer calculation. For an engine with a determined structure, under the condition of consistent vehicle working states, the flow rates of the fluid at each node on the flow path are the same. Therefore, the flow rates of the fluid at each heat transfer node on the flow path can be determined according to the vehicle operation state information without performing real simulation of the fluid state. Compared with the AMESim model, the cumbersome fluid state simulation process will no longer be needed.

[0036] Similarly, this simplified calculation idea can also be applied to the calculation of heat conduction between solids and the calculation of radiative heat dissipation on the outer surface of solids. For an engine with a determined structure, the heat conduction amount between adjacent solids can be considered to be directly related to the temperature difference between them, that is, it can be considered as a proportional function of the temperature difference. Therefore, this proportional coefficient can be determined, and compared with the AMESim model, the calculation of heat conduction between solids will be simplified. The combined specific heat of the two contacting solids can also be determined, so that when the heat conduction amount is determined, the temperature rise changes of the two contacting solids can be determined.

[0037] According to an embodiment of the present invention, a method for processing an engine physical model is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0038] Figure 2 is a flowchart of a method for processing an engine physical model according to an embodiment of the present invention, as Figure 2 shown, the method includes the following steps:

[0039] Step S202, based on the entity structure of the engine, construct a complex physical model of the engine, where the complex physical model includes entity elements corresponding to different parts in the entity structure, and connection elements connected to different entity elements. The connection elements include one of the following: heat conduction elements, heat exchange elements, and radiation elements.

[0040] The engine entity structure in the above steps may include different parts of the engine, such as supercharger, piston, crankshaft, connecting rod, bearing shell, cylinder head, engine block, oil pan, water circuit circulation, and cooling oil circuit circulation, etc. See Figure 4 for details, but not limited to this, and it can also be determined according to the actual entity structure of the engine.

[0041] The complex physical model in the above steps may be a detailed thermal management model of the engine built using simulation software. In an optional embodiment, it can be built based on the digital model parameters, attributes, and characteristic data of the engine and the peripheral cooling system, and taking the water circuit circulation and oil circuit circulation on the vehicle engine as the main line, and fully considering the heat exchange conditions at each node on the water and oil circuits. The characteristic data here mainly refers to the pressure drop-flow and heat dissipation characteristic data of the fluid at each node, such as the pressure drop-flow-heat dissipation characteristic data on the engine cooler, the pressure drop-flow-heat dissipation characteristic data on the radiator, etc. The heat transfer process between components on the engine is fully considered in the model, including heat conduction between solid and solid components, heat exchange between solid and fluid, heat exchange between solid and air, etc.

[0042] The components in the above steps can be specific parts of the engine, or components obtained by cutting a system or part due to the coexistence of multiple heat transfer forms for convenient description during modeling. For example, to simulate the heat transfer between the engine block and the crankcase oil mist and the heat transfer between the block and the combustion chamber, the engine block can be cut at the lower boundary of the cylinder barrel. The upper part is taken as one component, mainly describing the heat transfer between the block and the combustion chamber gas; the lower part is taken as another component, mainly describing the heat transfer between the block and the oil mist. Optionally, the components can be connected through heat conduction elements in AMESim to simulate the heat conduction between entities; the components can also be connected to fluids through heat transfer elements to simulate the heat transfer between solids and fluids, and the components can be connected to the external environment through radiation elements to simulate the heat radiation process.

[0043] The above heat conduction can be the heat transfer process between two solid entities. As long as the material properties, mass, temperature difference, centroid distance, contact area and other parameters of the two contacting objects are input into AMESim, the heat management model can calculate the heat transfer situation between the two solids.

[0044] The above heat transfer can be the heat transfer process between a solid and a fluid. Generally, the fluid cools the solid, and the ability of the fluid to carry away heat depends on parameters such as the properties of the fluid, the properties of the solid, the fluid flow rate, and the contact area. As long as these parameters are input into AMESim, the heat management model can calculate the heat transfer situation between the solid and the fluid.

[0045] The above radiation can be the situation where a solid radiates heat outward. As long as the solid property parameters, temperature, ambient temperature and other parameters are input into AMESim, the heat management model can calculate the heat radiation situation of the solid.

[0046] In the embodiment of the present invention, first, based on the physical structure of the engine, a vehicle thermal path physical model is built using simulation software such as AMESim fluid simulation software, such as a certain 15TD dual-motor hybrid vehicle (only considering engine cooling and not considering motor cooling). This model takes the engine water circuit and oil circuit as the main lines, the heat source comes from combustion heat release, taking into account the heat conduction and radiation heat dissipation between solid entities, and fully considering the heat absorption and heat dissipation processes in the water circuit and oil circuit cycles.

[0047] Water circuit part: AMESim is used to build a complete water circuit circulation path. For the key nodes in the water flow circulation, the pressure drop-flow characteristics of the water flow at this node are fully considered. For the nodes with water flow control functions, the control strategies of this node are also added. For example, water flow control strategies are added to water pumps, temperature control valves, thermostats, etc.;

[0048] Oil circuit part: The AMESim software was used to build a complete oil circuit loop. For the nodes on the oil circuit loop, the pressure drop-flow characteristics of the oil at these nodes were fully considered. Similarly, for the nodes with control functions for oil flow, the control strategies of these nodes were also added, such as adding the oil flow control strategy of the oil pump.

[0049] Heat exchange part: On the water circuit loop, for the nodes with heat dissipation or heat exchange characteristics, in addition to considering the pressure drop-flow characteristics of the water at these nodes, the heat dissipation or heat exchange conditions at these nodes were also considered. The heat dissipation mainly occurs through the radiator, and the heat exchange mainly considers the contact heat exchange between water and hot solids, including the contact heat exchange between the water in the engine water jacket and the inner wall of the solid, and the contact heat exchange between the water in the supercharger water channel and the inner wall of the solid; on the oil circuit loop, for the nodes with heat exchange characteristics, in addition to considering the pressure drop-flow characteristics of the oil at these nodes, the heat exchange conditions of the oil at these nodes were also considered, including the contact heat exchange between the oil in the engine oil passage and the inner wall of the solid, and the contact heat exchange between the oil in the supercharger oil passage and the inner wall of the solid. At the same time, the oil circuit heat exchange also considered the contact heat exchange between the oil and the outer surface of the hot solid, mainly referring to the splash cooling part of the oil on the hot body, such as the contact between the oil and the cylinder block surface, the contact between the oil and the piston surface, the contact between the oil and the crankshaft surface, etc. The oil circuit heat exchange also considered the heat exchange between the oil and the oil pan.

[0050] Solid heat conduction part: For the convenience of considering the convective heat transfer between the fluid and the solid during the model building process, the engine was cut into many entities during the modeling process. Therefore, the heat conduction problem between the solid entities was fully considered during the model building, and the external radiation heat dissipation problem of the solid outer surface was also considered.

[0051] Step S204: Merge some components in the complex physical model to obtain multiple merged modules, where the multiple modules are related to the water temperature and oil temperature of the engine.

[0052] Optionally, the multiple modules at least include: water block, radiator block, engine block, water flow block, oil block, and supercharger block. Among them, the water flow block is used to determine the water flow rate flowing through other modules.

[0053] The main idea of the reduction method of the present invention is to organize and combine some components of a complex thermal management model. The reduced-order model will no longer have the detailed structure of the original model. The main objective of constructing the reduced-order thermal management model or real-time model of the present invention is to calculate the water temperature and oil temperature through this model for other modules to use. Therefore, modules that can reflect the engine water temperature and oil temperature need to be retained in the reduced-order thermal management model. On this basis, the water in the engine can be synthesized into a water block that can represent the engine water temperature, and at the same time, the oil in the engine can be synthesized into an oil block that can represent the engine oil temperature; considering that the heat of water and oil comes from the engine block and the supercharger, the engine solid structure can be synthesized into an engine block, and the supercharger as a whole can be synthesized into a supercharger block. Through the analysis of the complex thermal management model, it can be seen that more than 90% of the heat dissipated by the engine is absorbed by the water, and the heat absorbed by the water is finally mainly dissipated by the radiator. Therefore, a radiator block is required in the reduced-order thermal management model. At the same time, the heat dissipation capacity of the radiator is related not only to external factors such as wind speed and fan, but also to the water flow rate through the radiator. Not only the radiator, but also the heat exchange capacity between the supercharger, engine and oil cooler and water is related to the water flow rate. Therefore, the reduced-order thermal management model should also retain the water flow rate block, which can output the water flow rate through the engine block, supercharger block, oil block and radiator block under different working conditions. Based on this idea, the complex physical model with detailed structure is reduced to a physical model including six structures: engine block, water block, oil block, supercharger block, radiator block and water flow rate block. Together with the input heat source module and ambient temperature module, the final reduced-order physical model consists of the above eight parts. There is the same heat exchange relationship between these eight parts as that on the objective actual machine, as shown in Figure 5 , these eight parts are closely related according to the heat transfer theory and the law of conservation of energy, and form a thermal management model that can perform real-time operations in the Simulink environment. Among them, the water flow rate block is mainly used to determine the water flow rate through other modules, as shown in Figure 6 .

[0054] Optionally, the input heat of the engine block, supercharger block and oil block includes: the heat input by the combustion heat source, the heat taken away by the water and the heat dissipated to the air; the input heat of the water block includes: the heat dissipated from the engine block to the water block, and the heat exchanged between the water block and the water flow rate block; the input temperature based on which the water temperature in the oil block is determined includes: the temperature of the oil block and the water temperature in the engine block; the input temperature based on which the water temperature in the supercharger block is determined includes: the temperature of the supercharger block and the water temperature in the engine block; the input temperature based on which the water temperature in the radiator block is determined includes: the temperature of the ambient air and the water temperature in the engine block.

[0055] In an alternative embodiment, for the engine block, the input heat is composed of three parts. One part is the heat input from the combustion heat source, one part is the heat carried away by water from the engine block, and the other part is the heat dissipated from the engine block to the air. The output is the temperature of the engine block, which is obtained by superimposing the integral value of the temperature change of the engine block on the basis of the initial temperature. The calculation formula for the temperature change of the engine block is as follows:

[0056]

[0057] Wherein, represents the temperature change of the engine block, Q h_combEng represents the heat input into the engine block from the combustion heat source, Q h_Enghtc represents the heat carried away by water in the engine block, Q h_EngAmb represents the heat dissipated from the engine block to the air, m Eng represents the mass of the engine block, C p_Eng represents the comprehensive average specific heat of the engine block;

[0058] Furthermore, the specific calculation formulas for Q h_combEng , Q h_combEng and Q h_EngAmb are as follows:

[0059] Q h_combEng = f(ω eng , tq eng ), wherein, ω eng represents the engine speed, tq eng is the engine torque;

[0060] Q h_Enghtc = hA htcEng (T eng - T htcEng ), wherein, hA htcEng is the heat transfer coefficient between the engine block and water, T eng is the engine block temperature, T htcEng is the temperature of the water block in the engine;

[0061] Q h_EngAmb = hA EngAmb (T eng - T amb ), wherein, hA EngAmb is the heat transfer coefficient between the engine block and the environment, T eng is the engine block temperature, T amb is the ambient temperature.

[0062] For the supercharger block, the input heat is composed of three parts. One part is the heat input by combustion, another part is the heat carried away by water from the supercharger block, and the remaining part is the heat dissipated from the supercharger block to the air. The output is the temperature of the supercharger block body, which is obtained by superimposing the integral value of the temperature change of the supercharger block on the basis of the initial temperature. The calculation formula for the temperature change of the supercharger block is as follows:

[0063]

[0064] Among them, is the temperature change of the supercharger block, Q h_combTurbo is the heat input into the supercharger block by the combustion heat source, Q h_Turbohtc is the heat carried away by water in the supercharger block, Q h_TurboAmb is the heat dissipated into the air in the supercharger block, m Turbo is the mass of the supercharger, C p_Turbo is the comprehensive average specific heat of the supercharger;

[0065] Furthermore, Q h_Turbohtc 、Q h_TurboAmb The specific calculation formulas are as follows:

[0066] Among them, ω eng represents the engine speed, tq eng is the engine torque;

[0067] Q h_Turbohtc =hA htcTurbo (T turbo -T htcTurbo ), where hA htcTurbo is the heat transfer coefficient between the supercharger block and water, T turbo is the temperature of the supercharger block, T htcTurbo is the water temperature inside the supercharger block;

[0068] Q h_TurboAmb =hA TurboAmb (T turbo -T amb ), hA TurboAmb is the heat transfer coefficient between the supercharger and the ambient air, T turbo is the supercharger block temperature, T amb is the ambient temperature.

[0069] For the oil block, the input heat is composed of three parts. One part is the heat input by combustion, another part is the heat carried away by water from the oil block, and the remaining part is the heat dissipated from the oil block to the air. The output is the temperature of the oil block, which is obtained by superimposing the integral value of the temperature change of the oil block on the basis of the initial temperature. The calculation formula for the temperature change of the oil block is as follows:

[0070]

[0071] Among them, is the temperature change of the oil block, and Q h_combSump is the heat input from the combustion heat source into the oil block, and Q h_oilHxhtc is the heat exchange amount between the oil block and water, and Q h_sumpAmb is the heat dissipated from the oil block to the ambient air, m Sump is the mass of the oil block, and C p_Sump is the comprehensive specific heat of the oil block;

[0072] Furthermore, Q h_combsump 、Q h_oilHxhtc 、Q h_sumpAmb The specific calculation formulas are as follows:

[0073] Q h_combsump ==f(ω eng , tq eng ), where ω eng represents the engine speed, and tq eng is the engine torque;

[0074] Q h_oilHxhtc = hA htcoilHx (T sump -T htcOilHx ), where hA htcOilHx is the heat transfer coefficient between the oil block and water, T sump is the temperature of the oil block, and T htcOilHx is the water temperature inside the oil block;

[0075] Q h_sumpAmb = hA sumpAmb (T sump -T amb ), where hA sumpAmb is the heat transfer coefficient between the oil block and the ambient air, T sump is the temperature of the oil block, and T amb is the temperature of the ambient air.

[0076] For the water block, the input heat is composed of two parts. One part is the heat dissipated from the engine block to the water block, and the other part is the heat exchanged between the water block and the water outside the engine; the output is the temperature of the engine water block, and this output temperature is obtained by superimposing the integral value of the temperature change of the water block on the basis of the initial temperature. The calculation formula for the temperature change of the water block is as follows:

[0077]

[0078] Among them, is the temperature change of the engine water block, and Q h_EnghtcThe heat dissipated from the engine block to the water block, Q e_htcEng The heat exchange amount between the engine water block and the water outside the engine water block, m htcEng The temperature of the engine water block, C p_htcCool The comprehensive specific heat of the engine water block;

[0079] Furthermore, Q h_Enghtc 、Q e_htcEng The specific calculation formulas are as follows:

[0080] Q h_Enghtc =hA htcEng (T eng -T htcEng ), where hA htcEng is the heat transfer coefficient between the engine block and the water, T eng is the temperature of the engine block, T htcEng is the temperature of the water block inside the engine;

[0081] Q e_htcEng =w htcEng C p_htcCool (T htcEng -T htcPump ), where w htc_Eng is the mass of the water flow through the engine, C p_htcCool is the comprehensive specific heat of the engine water block, T htcEng is the temperature of the water block inside the engine, T htcPump is the water temperature outside the engine water block;

[0082] Furthermore, the specific calculation formula of T htcPump is as follows:

[0083]

[0084] where T htcOilHx is the water temperature inside the oil block, T htcRad is the water temperature inside the radiator block, T htcTurbo is the water temperature of the supercharger block, T htcEng is the water temperature inside the engine block, w htcOilHx is the water flow rate of the oil cooler, w htcRad is the water flow rate of the radiator, w htcTurbo is the water flow rate of the supercharger, w htcEng is the water flow rate of the engine block, w htcpump The total water flow rate through the water pump.

[0085] In addition, the calculation formula of the water temperature inside the oil block is as follows:

[0086]

[0087] The calculation formula of the water temperature inside the radiator block is as follows:

[0088]

[0089] The water temperature in the supercharger block is calculated as follows:

[0090]

[0091] By combining all the above formulas, the model structure of the reduced-order thermal management model can be established.

[0092] Step S206, inputting the operating parameters of the engine under different working conditions into the complex physical model, and determining the target spectrum parameters corresponding to the multiple modules, wherein the target spectrum parameters at least include: heat transfer coefficient, thermal conductivity, radiation coefficient and fluid flow parameter.

[0093] The model structure of the reduced-order thermal management model can be constructed through the above steps, but the included spectrum parameters cannot be given directly, nor can they be obtained through actual machine testing. These parameters that cannot be determined are as follows:

[0094] Heat transfer coefficient hA between engine block and water under different water flows htcEng , heat transfer coefficient between engine and air at different vehicle speeds hA EngAmb ;

[0095] Heat transfer coefficient hA between oil block and water under different water flows htcoilHx , the heat transfer coefficient between the engine and the air at different vehicle speeds hA SumpAmb ;

[0096] Heat transfer coefficient hA between supercharger and water under different water flows htcTurbo , the heat exchange coefficient between the supercharger and the air at different vehicle speeds hA TurboAmb ;

[0097] The heat transfer coefficient between the radiator and the air under different water flow and different vehicle speeds hA htcRad ;

[0098] The comprehensive specific heat of the engine block C p_Eng 、Comprehensive specific heat of oil block C p_sump 、Comprehensive specific heat of supercharger C p_Turbo ;

[0099] Water flow w flowing into the engine body under different working conditions htcEng , water flow rate w flowing into the supercharger htcTurbo , water flow rate w flowing into the radiator htcRad , water flow into the oil cooler w htcoilHx .

[0100] The operating parameters in the above steps are five variables: engine speed, torque, ambient temperature, vehicle speed, and initial engine temperature.

[0101] In an alternative embodiment, after the thermal management model is built, the model can be simulated to determine the heat transfer process on the built physical model, facilitating the capture of the heat exchange amount between the fluid and the solid, the heat conduction amount between the solids, the radiant heat dissipation amount of the solid, as well as the temperature rise conditions of the fluid and the solid and the flow state data of the fluid under various vehicle operating conditions and other target pulse spectrum parameters. Through the analysis of the captured data, on the one hand, the secondary factors on the model heat flow can be ignored and the main factors on the model heat flow can be focused on to optimize the engine modeling segmentation method; on the other hand, through the Design Of Experiment (abbreviated as DOE) experimental design, the proportional heat transfer coefficient between the fluid and the hot solid, the proportional heat conduction coefficient between the solids, the radiant proportional coefficient of the solid, etc. in the model (i.e., the reduced-order thermal management model) divided by the new segmentation method can be determined, and the flow parameters of the fluid at the heat exchange nodes under different vehicle states can also be determined.

[0102] First, a DOE experimental plan is formulated with the input of the reduced-order thermal management model as the factor. In order to enable the future reduced-order thermal management model to adapt to a larger working range, the DOE plan will cover as much as possible all the working ranges of the operating parameters. The DOE plan of the case described in the present invention has selected a total of 20 test combinations, as shown in Table 1 below:

[0103] Table 1 DOE experimental test combinations

[0104]

[0105]

[0106] Run the 1D complex thermal management model with the above DOE plan. At each test combination, the water temperature and oil temperature need to reach equilibrium, and record the process heat data and process temperature data absorbed by the whole engine, the whole oil pan, the water inside the engine, and the whole supercharger during the whole process. At the same time, record the water flow rates through the engine block, supercharger, oil cooler, and radiator under each working condition.

[0107] Taking the engine block as an example, by recording the heat absorbed by the whole engine and the temperature change value of the whole engine over a period of time, and then dividing the two, the comprehensive specific heat value of the engine can be obtained;

[0108] Taking the engine block as an example, by recording the process data of the heat directly dissipated from the engine to water, the process temperature data of the whole engine, and the temperature data of the water in the engine at the temperature balance of a DOE working condition, and dividing the heat exchange value between the two per unit time by the temperature difference between the two, the heat transfer coefficient of the water in the engine under this working condition can be obtained. The calculation method of the heat transfer coefficient under other working conditions is the same as above.

[0109] After determining all the undetermined parameters of the reduced-order heat management model by applying the 1D complex heat management model simulation, the reduced-order heat management model is formed. At this time, the first thing we need to do is to check the accuracy of the reduced-order heat management model. The WLTC measured data of the whole vehicle can be input into this reduced-order heat management model. If the model output can meet the accuracy requirements compared with the actual situation, it can be considered that the accuracy of the reduced-order heat management model meets the standard and can be integrated into the virtual calibration model for virtual calibration application. Otherwise, the accuracy of the real-time model needs to be adjusted. There are two methods to adjust the reduced-order heat management model. One is to directly fine-tune the reduced-order heat management model, and the other is to adjust the accuracy of the 1D complex heat management model and then re-reduce the order until the accuracy meets the standard and can be used for virtual calibration. The comparison between the reduced-order heat management model shown in the case of the present invention and the measured data mainly focuses on the water temperature. As Figure 7 shown, from top to bottom, it can be divided into: the comparison curve between the simulated water temperature of the reduced-order model (T_htcEng_degC) and the measured water temperature, the curve of the difference between the measurement and the simulation, and the engine speed curve.

[0110] Step S208, combine multiple modules and target pulse spectrum parameters to generate a reduced-order physical model of the engine.

[0111] In an alternative embodiment, the final reduced-order physical model is obtained by inputting the parameter values of the target pulse spectrum parameters into the model structure determined by multiple modules.

[0112] In the embodiment of the present invention, first, based on the physical structure of the engine, a complex physical model of the engine is constructed. Then, some components in the complex physical model are merged to obtain multiple merged modules. And the operating parameters of the engine under different working conditions are input into the complex physical model to determine the target pulse spectrum parameters corresponding to the multiple modules. Finally, the multiple modules and the target pulse spectrum parameters are combined to generate a reduced-order physical model of the engine. It is easy to note that the complex physical model is constructed based on the physical structure of the engine and is reduced-order processed based on the operating parameters of the engine under different working conditions, achieving the purpose of meeting the real-time requirements of the model for vehicle virtual calibration (controller-in-the-loop), thus realizing the technical effect of simplifying the model, and further solving the technical problem that the physical model of the engine constructed in the related art can ensure the model accuracy but the operating speed cannot meet the real-time requirements of the model for virtual calibration.

[0113] Optionally, based on the physical structure of the engine, constructing a complex physical model of the engine includes: determining multiple nodes on the water circuit and oil circuit of the engine based on the physical structure of the engine; constructing a complex physical model based on the digital model parameters, attributes, and characteristic data of each node, and the heat transfer process of each node, where the characteristic data is used to characterize the pressure drop, flow rate, and heat dissipation characteristic data of the fluid at each node.

[0114] In an alternative embodiment, based on the digital model parameters, attributes, and characteristic data of the engine and the peripheral cooling system, the physical structure of the engine can be divided into structures such as a supercharger, piston, crankshaft, cylinder head, engine block, oil pan, water circuit, and cooling oil circuit. Based on this, a physical model is built. The built model takes the engine water circuit and oil circuit as the main line, the heat source comes from combustion heat release, taking into account the heat conduction and radiation heat dissipation between solid entities, and fully considering the heat absorption and heat dissipation processes on the water circuit and oil circuit. The built model can include the following modules: a supercharger module, a piston module, a crankshaft module, a cylinder head module, an engine block module, an oil pan module, a water circuit module, and a cooling oil circuit module.

[0115] Optionally, after constructing a complex physical model of the engine based on the physical structure of the engine, the method further includes: when the engine is operating under a preset working condition, collecting the first measured temperature of multiple temperature measurement points on the engine through a temperature sensor; when the complex physical model is operating under a preset working condition, obtaining the first simulation temperature of multiple temperature measurement points output by the complex physical model; determining whether the accuracy of the complex physical model reaches a first preset accuracy based on the deviation between the first measured temperature and the first simulation temperature; and adjusting the pulse spectrum parameters included in the complex physical model when the accuracy of the complex physical model does not reach the first preset accuracy.

[0116] To ensure that the model accuracy of the reduced-order thermal management model obtained after the order reduction process meets the requirements and to reduce the adjustment time of the parameters of the reduced-order thermal management model, after generating the complex thermal management model of the engine in the above steps, the accuracy of the thermal management model can be determined through simulation, that is, by providing known input and output information, inputting the input information into the complex thermal management model to obtain the model output information, and comparing the known output information with the model output information to further obtain the accuracy of the complex thermal management model. Compare the accuracy of the complex thermal management model with the first preset accuracy, that is, the target accuracy required by the user (which can be set artificially). If the accuracy of the complex thermal management model is greater than or equal to the first preset accuracy, it is determined that the model accuracy of the complex thermal management model meets the requirements, and the construction process of the complex thermal management model ends; if the accuracy of the complex thermal management model is less than the first preset accuracy, it is determined that the model accuracy of the complex thermal management model does not meet the requirements, and the pulse spectrum parameters of the complex thermal management model need to be adjusted. Repeat the above steps until the accuracy of the finally determined complex thermal management model meets the requirements.

[0117] Here, in order to verify the accuracy of the complex thermal management model, thermocouples are arranged at typical positions in the water circuit and oil circuit of the actual vehicle. A total of 6 temperature measurement points are mainly arranged in the water circuit, namely at the inlet of the engine mechanical water pump, the outlet of the thermostat, the inlet of the radiator, the outlet of the radiator, the inlet of the air-conditioning water, and the outlet of the air-conditioning water. One temperature measurement point is mainly arranged in the oil circuit. The oil temperature of the oil pan is measured by replacing the oil pan bolt with a thermocouple. The actual vehicle is run on the chassis dynamometer under the WLTC (World Light Vehicle Test Cycle) cycle while the temperatures of each measurement point are collected. Then, the thermal management model is run under the WLTC condition, and the deviation between the simulation value and the measured value at the measurement point is compared to further check and confirm the accuracy of the model and adjust the model accuracy.

[0118] In the embodiment of the present invention, the water temperature accuracy target of the one-dimensional thermal management model can be set to ±6 degrees, and the oil temperature accuracy target can be set to ±8 degrees. If the temperature deviation at the water temperature and oil temperature measurement points from the measured data is within the above accuracy range, it is considered that the accuracy of the one-dimensional complex thermal management model meets the standard, and we will proceed to the next step of order reduction. Otherwise, the model accuracy needs to be further adjusted.

[0119] Optionally, after combining multiple modules and target pulse spectrum parameters to generate a reduced-order physical model of the engine, the method further includes: when the engine is operating under a preset working condition, collecting second measured temperatures of multiple temperature measurement points on the engine through a temperature sensor; when the reduced-order physical model is operating under a preset working condition, obtaining second simulated temperatures of the multiple temperature measurement points output by the reduced-order physical model; determining whether the accuracy of the reduced-order physical model reaches a second preset accuracy based on the deviation between the second measured temperature and the second simulated temperature; and adjusting the pulse spectrum parameters included in the reduced-order physical model when the accuracy of the reduced-order physical model does not reach the second preset accuracy.

[0120] To ensure that the model accuracy of the reduced-order thermal management model meets the requirements, after generating the corresponding reduced-order thermal management model in the above steps, the model accuracy of the reduced-order thermal management model can be determined through simulation, that is, given known input and output information, inputting the input information into the reduced-order thermal management model to run to obtain model output information, and comparing the known output information and the model output information to obtain the accuracy of the reduced-order thermal management model. Comparing the accuracy of the reduced-order thermal management model with the second preset accuracy, that is, the target accuracy required by the user (which can be artificially set by the user), if the accuracy of the reduced-order thermal management model is greater than or equal to the second preset accuracy, it is determined that the accuracy of the reduced-order thermal management model meets the requirements, and the reduced-order processing flow ends; if the accuracy of the reduced-order thermal management model is less than the second preset accuracy, it is determined that the accuracy of the reduced-order thermal management model does not meet the requirements, and the pulse spectrum parameters of the reduced-order thermal management model need to be adjusted, and the above steps are repeated until the accuracy of the finally determined reduced-order thermal management model meets the requirements.

[0121] Figure 3 is a flowchart of an optional thermal management model reduction method according to an embodiment of the present invention, as Figure 3 shown, the method includes the following steps:

[0122] Step S302, based on the physical structure of the engine, construct a 1D thermal management model of the engine.

[0123] The physical structure of the engine in the above steps may include a supercharger, a piston, a crankshaft, a cylinder head, a cylinder block, an oil pan, a water circuit circulation, and a cooling oil circuit circulation, specifically see Figure 4 , but not limited to this, and can also be determined according to the actual physical structure of the engine. Use existing model construction software to construct a 1D thermal management model, such as AMESim fluid simulation software, but not limited to this.

[0124] The 1D thermal management model in the above steps may be a vehicle thermal path physical model built using simulation software. In an optional embodiment, the model can be built according to the pre-designed accuracy requirements, or the accuracy can be confirmed after construction, and the parameters in the model can be adjusted.

[0125] The 1D thermal management model in the above steps may include multiple modules corresponding to each entity structure, namely, a supercharger module, a piston module, a crankshaft module, a cylinder head module, a cylinder block module, an oil pan module, a water circuit circulation module, and a cooling oil circuit circulation module, but is not limited thereto, and may also be determined according to the entity structure of the actual engine.

[0126] Step S304: Perform simulation and accuracy verification on the built 1D model.

[0127] For the engine 1D thermal management model in the above steps, the accuracy requirements can be designed in advance, or the accuracy can be verified after it is built. To ensure that the model accuracy of the reduced-order thermal management model obtained after the reduced-order processing meets the requirements and reduce the adjustment time of the parameters of the reduced-order thermal management model, after the built 1D model of the engine is generated in the above steps, the built 1D model can be simulated to determine the model accuracy, that is, given the known input and output information, input the input information into the built 1D model to run to obtain the model output information, and compare the known output information with the model output information to obtain the accuracy of the built 1D model.

[0128] Step S306: Determine whether the accuracy of the built 1D model meets the standard.

[0129] Compare the accuracy of the built 1D model with the first preset accuracy, that is, the first target accuracy required by the user (which can be set manually by the user). If the accuracy of the built 1D model is greater than or equal to the first preset accuracy, it is determined that the accuracy of the built 1D model meets the standard, and the thermal management model construction process ends; if the accuracy of the built 1D model is less than the first preset accuracy, it is determined that the accuracy of the built 1D model does not meet the standard, and the pulse spectrum parameters of the thermal management model need to be adjusted, and step S304 is executed until the accuracy of the finally determined built 1D model meets the standard.

[0130] Step S308: Analyze the heat flow distribution through the simulation of the built 1D model.

[0131] Optionally, determine the target pulse spectrum parameters by conducting an experimental design test on the thermal management model. That is, conduct a DOE experimental design test on the thermal management model to determine the heat transfer coefficient, thermal conductivity, radiation coefficient, and fluid flow rate parameters.

[0132] After the thermal management model in the above steps is built, the heat transfer process on the built physical model can be determined through the simulation of the built 1D model, which is convenient for capturing the heat exchange amount between the fluid and the solid, the heat conduction amount between the solids, the radiant heat dissipation amount of the solid, as well as the temperature rise conditions of the fluid and the solid and the fluid flow state data under various vehicle operating conditions and other target pulse spectrum parameters.

[0133] Step S310: Optimize the composition of the modules in the model.

[0134] Through the analysis of the captured data, on the one hand, the secondary factors on the model heat flow can be ignored, and the main factors on the model heat flow can be focused on. By using the heat transfer parameters obtained through simulation, some or all of the supercharger module, piston module, crankshaft module, cylinder head module, engine block module, oil pan module, water circuit circulation module, and cooling oil circuit circulation module can be merged to obtain the modules included in the reduced-order heat management model, which are the water flow characteristic module, radiator module, engine mass body module, engine coolant module, oil block, and supercharger module, but not limited to this.

[0135] Step S320, building the reduced-order heat management model.

[0136] In the above steps, after performing the DOE experimental design detection on the heat management model and determining the target pulse spectrum parameters, namely the heat transfer coefficient, thermal conductivity, radiation coefficient, and fluid flow parameters, the six new merged modules and the target pulse spectrum parameters obtained after simulation can be integrated to obtain the reduced-order heat management model. At this time, the model structure of the reduced-order heat management model is the six new merged modules, and the model parameters are the target pulse spectrum parameters.

[0137] Step S312, generating the DOE test specification.

[0138] Step S314, 1D model simulation.

[0139] Through the DOE experimental design, parameters such as the proportional heat transfer coefficient between the fluid and the hot solid, the proportional thermal conductivity between the solids, and the radiation proportional coefficient of the solid in the model (i.e., the reduced-order heat management model) divided in the new segmentation method can be determined, and target pulse spectrum parameters such as the fluid flow parameters at the heat transfer nodes under different vehicle conditions can also be determined.

[0140] Step S316, the 1D model simulation ends.

[0141] Step S322, pulse spectrum confirmation of the reduced-order heat management model.

[0142] Step S324, simulation and accuracy confirmation of the reduced-order heat management model.

[0143] After generating the corresponding reduced-order heat management model in the above steps, in order to ensure that the model accuracy of the reduced-order heat management model meets the requirements, after generating the corresponding reduced-order heat management model in the above steps, the reduced-order heat management model can be simulated to determine the model accuracy, that is, given the known input and output information, the input information is input into the reduced-order heat management model to run and obtain the model output information, and the known output information and the model output information are compared to obtain the accuracy of the reduced-order heat management model.

[0144] Step S326, determining whether the accuracy of the built reduced-order heat management model meets the standard.

[0145] Compare the accuracy of the reduced-order thermal management model with the second preset accuracy, i.e., the second target accuracy required by the user (which can be artificially set by the user). If the accuracy of the reduced-order thermal management model is greater than or equal to the second preset accuracy, it is determined that the accuracy of the reduced-order thermal management model meets the standard, and the reduced-order processing flow ends; if the accuracy of the reduced-order thermal management model is less than the second preset accuracy, it is determined that the accuracy of the reduced-order thermal management model does not meet the standard, and the pulse spectrum parameters of the reduced-order thermal management model need to be adjusted, and step S324 is executed until the accuracy of the finally determined reduced-order thermal management model meets the standard.

[0146] Step S328, the reduced-order thermal management model is completed.

[0147] According to an embodiment of the present invention, there is also provided a processing device for an engine physical model. This device can execute the processing method of the engine physical model in the above embodiment. The specific implementation scheme and application scenario are the same as those in the above embodiment, and will not be elaborated here.

[0148] Figure 8 is a schematic diagram of a processing device for an engine physical model according to an embodiment of the present invention, as Figure 8 shown. The device includes:

[0149] A construction module 82, configured to construct a complex physical model of the engine based on the entity structure of the engine. The complex physical model includes entity elements corresponding to different parts in the entity structure, and connection elements connected to different entity elements. The connection elements include one of the following: heat conduction elements, heat exchange elements, and radiation elements;

[0150] A merging module 84, configured to merge some elements in the complex physical model to obtain multiple merged modules, where the multiple modules have an associated relationship with the water temperature and oil temperature of the engine;

[0151] A determination module 86, configured to input the operating parameters of the engine under different working conditions into the complex physical model, and determine the target pulse spectrum parameters corresponding to the multiple modules, where the target pulse spectrum parameters at least include: heat transfer coefficient, thermal conductivity, radiation coefficient, and fluid flow parameters;

[0152] A generation module 88, configured to combine the multiple modules and the target pulse spectrum parameters to generate a reduced-order physical model of the engine.

[0153] Optionally, the construction module includes: a determination unit, configured to determine multiple nodes on the water circuit and oil circuit of the engine based on the entity structure of the engine; a construction unit, configured to construct a complex physical model based on the digital model parameters, attributes, and characteristic data of each node, and the heat exchange process of each node, where the characteristic data is used to characterize the pressure drop, flow rate, and heat dissipation characteristic data of the fluid at each node.

[0154] Optionally, the device further includes: a first acquisition module, configured to collect first measured temperatures of multiple temperature measurement points on the engine through a temperature sensor when the engine operates under a preset working condition; a first obtaining module, configured to obtain first simulated temperatures of the multiple temperature measurement points output by a complex physical model when the complex physical model operates under the preset working condition; a first determination module, configured to determine whether the accuracy of the complex physical model reaches a first preset accuracy based on the deviation between the first measured temperature and the first simulated temperature; a first adjustment module, configured to adjust the pulse spectrum parameters included in the complex physical model when the accuracy of the complex physical model does not reach the first preset accuracy.

[0155] Optionally, the device further includes: a second acquisition module, configured to collect second measured temperatures of multiple temperature measurement points on the engine through a temperature sensor when the engine operates under a preset working condition; a second obtaining module, configured to obtain second simulated temperatures of the multiple temperature measurement points output by a reduced-order physical model when the reduced-order physical model operates under the preset working condition; a second determination module, configured to determine whether the accuracy of the reduced-order physical model reaches a second preset accuracy based on the deviation between the second measured temperature and the second simulated temperature; a second adjustment module, configured to adjust the pulse spectrum parameters included in the reduced-order physical model when the accuracy of the reduced-order physical model does not reach the second preset accuracy.

[0156] According to an embodiment of the present invention, there is also provided a computer-readable storage medium, where the computer-readable storage medium includes a stored program, and when the program runs, it controls a device where the computer-readable storage medium is located to execute the processing method of the thermal management model in the above embodiment.

[0157] According to an embodiment of the present invention, there is also provided a processor, where the processor is used to run a program, and when the program runs, it executes the processing method of the thermal management model in the above embodiment.

[0158] According to an embodiment of the present invention, there is also provided a vehicle, including the reduced-order physical model in the above embodiment.

[0159] In the above embodiments of the present invention, the descriptions of the respective embodiments have their own focuses. For parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0160] In several embodiments provided by the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are merely illustrative. For example, the division of the units can be a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the couplings or direct couplings or communication connections shown or discussed with each other can be through some interfaces. The indirect couplings or communication connections of units or modules can be in electrical or other forms.

[0161] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0162] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0163] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention. The foregoing storage medium includes: USB flash drives, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), mobile hard disks, magnetic disks or optical discs and other various media that can store program codes.

[0164] The above is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A processing method for an engine physical model, characterized in that Including: Based on the physical structure of the engine, a complex physical model of the engine is constructed. Among them, the complex physical model includes entity elements corresponding to different parts in the physical structure, and connection elements connected to different entity elements. The connection elements include one of the following: heat conduction elements, heat exchange elements, and radiation elements; Some elements in the complex physical model are merged to obtain multiple merged modules. Among them, the multiple modules have an associated relationship with the water temperature and oil temperature of the engine. The multiple modules include an engine block, a water block, an oil block, a supercharger block, a radiator block, a water flow block, a heat source module, and an ambient temperature module. The engine block is obtained by synthesizing the solid structure of the engine. The water block is obtained by synthesizing the water in the engine. The oil block is obtained by synthesizing the oil in the engine. The supercharger block is obtained by synthesizing the entire supercharger. The water flow block is used to output the water flow passing through the engine block, the supercharger block, the oil block, and the radiator block under different working conditions; The operating parameters of the engine under different working conditions are input into the complex physical model to determine the target pulse spectrum parameters corresponding to the multiple modules. Among them, the operating parameters at least include: engine speed, torque, ambient temperature, vehicle speed, and initial engine temperature. The target pulse spectrum parameters at least include: heat transfer coefficient, thermal conductivity, radiation coefficient, and fluid flow parameters. Among them, the heat transfer coefficient at least includes: the heat transfer coefficient between the supercharger and water under different water flows, the heat transfer coefficient between the supercharger and air under different vehicle speeds, and the heat transfer coefficient between the radiator and air under different water flows and different vehicle speeds; The multiple modules and the target pulse spectrum parameters are combined to generate a reduced-order physical model of the engine; Among them, constructing the complex physical model of the engine based on the physical structure of the engine includes: determining multiple nodes on the water circuit and oil circuit of the engine based on the physical structure of the engine; constructing the complex physical model based on the digital model parameters, attributes, and characteristic data of each node, and the heat exchange process of each node. Among them, the characteristic data is used to characterize the pressure drop, flow rate, and heat dissipation characteristic data of the fluid at each node.

2. The method according to claim 1, characterized in that, The input heat of the engine block, the supercharger block, and the oil block includes: the heat input by the combustion heat source, the heat taken away by water, and the heat dissipated to air; the input heat of the water block includes: the heat dissipated from the engine block to the water block, and the heat exchanged between the water block and the water flow block; the input temperature based on which the water temperature in the oil block is determined includes: the temperature of the oil block and the water temperature in the engine block; the input temperature based on which the water temperature in the supercharger block is determined includes: the temperature of the supercharger block and the water temperature in the engine block; the input temperature based on which the water temperature in the radiator block is determined includes: the temperature of the ambient air and the water temperature in the engine block.

3. The method according to claim 1, wherein After constructing the complex physical model of the engine based on the physical structure of the engine, the method further includes: When the engine operates under a preset working condition, collect the first measured temperatures of multiple temperature measurement points on the engine through a temperature sensor; When the complex physical model operates under the preset working condition, obtain the first simulated temperatures of the multiple temperature measurement points output by the complex physical model; Based on the deviation between the first measured temperature and the first simulated temperature, determine whether the accuracy of the complex physical model reaches a first preset accuracy; When the accuracy of the complex physical model does not reach the first preset accuracy, adjust the pulse spectrum parameters included in the complex physical model.

4. The method according to claim 1, wherein After combining the multiple modules and the target pulse spectrum parameters to generate a reduced-order physical model of the engine, the method further includes: When the engine operates under a preset working condition, collect the second measured temperatures of multiple temperature measurement points on the engine through a temperature sensor; When the reduced-order physical model operates under the preset working condition, obtain the second simulated temperatures of the multiple temperature measurement points output by the reduced-order physical model; Based on the deviation between the second measured temperature and the second simulated temperature, determine whether the accuracy of the reduced-order physical model reaches a second preset accuracy; When the accuracy of the reduced-order physical model does not reach the second preset accuracy, adjust the pulse spectrum parameters included in the reduced-order physical model.

5. A processing device for an engine physical model, characterized in that, including: A construction module, configured to construct a complex physical model of the engine based on the physical structure of the engine. The complex physical model includes entity elements corresponding to different parts in the physical structure, and connection elements connected to different entity elements. The connection elements include one of the following: a heat conduction element, a heat exchange element, and a radiation element; A merging module, configured to merge some elements in the complex physical model to obtain multiple merged modules. The multiple modules have an associated relationship with the water temperature and oil temperature of the engine. The multiple modules include an engine block, a water block, an oil block, a supercharger block, a radiator block, a water flow block, a heat source module, and an ambient temperature module. The engine block is obtained by synthesizing the solid structure of the engine. The water block is obtained by synthesizing the water in the engine. The oil block is obtained by synthesizing the oil in the engine. The supercharger block is obtained by synthesizing the overall supercharger. The water flow block is configured to output the water flow passing through the engine block, the supercharger block, the oil block, and the radiator block under different working conditions; A determination module, configured to input the operating parameters of the engine under different working conditions into the complex physical model, and determine the target pulse spectrum parameters corresponding to the multiple modules. The operating parameters at least include: engine speed, torque, ambient temperature, vehicle speed, and initial engine temperature. The target pulse spectrum parameters at least include: heat transfer coefficient, thermal conductivity, radiation coefficient, and fluid flow parameters. The heat transfer coefficient at least includes: the heat transfer coefficient between the supercharger and water under different water flows, the heat transfer coefficient between the supercharger and air under different vehicle speeds, and the heat transfer coefficient between the radiator and air under different water flows and different vehicle speeds; A generation module, configured to combine the plurality of modules and the target pulse spectrum parameters to generate a reduced-order physical model of the engine; Wherein, the device is further configured to: determine a plurality of nodes on the water circuit and the oil circuit of the engine based on the physical structure of the engine; construct the complex physical model based on the digital model parameters, attributes and characteristic data of each node, and the heat exchange process of each node, wherein the characteristic data is used to characterize the pressure drop, flow rate and heat dissipation characteristic data of the fluid at each node.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program runs, it controls the device where the computer-readable storage medium is located to execute the processing method of the engine physical model according to any one of claims 1 to 4.

7. A processor, characterized in that, The processor is configured to run a program, wherein, when the program runs, it executes the processing method of the engine physical model according to any one of claims 1 to 4.

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